DocumentCode
3364833
Title
Intelligent FPGA based system for shape recognition
Author
Pedrino, Emerson C. ; Morandin, Orides, Jr. ; Kato, Edilson R R ; Roda, Valentin O.
Author_Institution
Dept. of Comput. Sci., Fed. Univ. of Sao Carlos, Sao Carlos, Brazil
fYear
2011
fDate
13-15 April 2011
Firstpage
197
Lastpage
202
Abstract
Mathematical morphology supplies powerful tools for low level image analysis, with applications in many areas. In this paper, the development of a novel reconfigurable hardware using a genetic algorithm and a pipeline architecture is proposed for the task of shape recognition in binary images. For the recognition process, a large sized convex structuring element representing the object shape to be recognized is decomposed into the architecture stages. Each stage can handle structuring elements of a limited size. In this approach, a genetic algorithm was used to decompose this structuring element. Thus, a simple erosion performed in each stage is used to detect the goal object. The hardware is capable of processing binary images at high speed. The developed system is based on FPGAs. Our approach represents an intelligent mechanism to reconfigure the pipeline architecture, it is different from other systems found in the literature, and the obtained results are promising.
Keywords
field programmable gate arrays; genetic algorithms; mathematical morphology; object detection; pipeline processing; reconfigurable architectures; shape recognition; binary image; genetic algorithm; intelligent FPGA based system; large sized convex structuring element; low level image analysis; mathematical morphology; object detection; object shape; pipeline architecture; reconfigurable hardware; shape recognition; Biological cells; Field programmable gate arrays; Genetic algorithms; Genetics; Pipelines; Pixel; Shape;
fLanguage
English
Publisher
ieee
Conference_Titel
Programmable Logic (SPL), 2011 VII Southern Conference on
Conference_Location
Cordoba
Print_ISBN
978-1-4244-8847-6
Type
conf
DOI
10.1109/SPL.2011.5782648
Filename
5782648
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